Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A non-transitory computer readable medium comprising instructions which, when executed by one or more hardware processors, cause performance of operations comprising: determining a first set of one or more attributes of a first system to be monitored; identifying a first probe, of a plurality of probes, that includes functionality to monitor systems with a second set of one or more attributes; determining there is an overlap between one or more attributes of the first set of attributes and one or more attributes of the second set of attributes; responsive at least to determining that there is the overlap between the one or more attributes of the first set of attributes and the one or more attributes of the second set of attributes: selecting the first probe for monitoring the first system; detecting a first set of data from the first system using the first probe.
The invention relates to automated system monitoring using configurable probes. The problem addressed is efficiently selecting appropriate monitoring tools for diverse systems with varying attributes, ensuring accurate and relevant data collection without manual intervention. The solution involves a computer-readable medium storing instructions for a monitoring system. The system first determines the attributes of a target system to be monitored, such as operating system type, network protocols, or hardware specifications. It then identifies available probes, each designed to monitor systems with specific attribute sets. The system compares the target system's attributes with each probe's supported attributes to find overlaps, indicating compatibility. When a match is found, the system selects the probe and uses it to collect data from the target system. This approach ensures that only probes capable of monitoring the system's attributes are deployed, improving monitoring accuracy and reducing configuration errors. The system dynamically adapts to different systems by leveraging attribute-based probe selection, eliminating the need for manual probe assignment. This method enhances scalability and reliability in monitoring heterogeneous environments.
2. The medium of claim 1 , wherein the first set of attributes of the first system comprises at least one of: (a) an operating system, (b) a software application, and (c) an issue associated with the first system.
This invention relates to a system for managing and analyzing attributes of computing systems to improve performance, security, or functionality. The system collects and processes attributes from multiple computing systems to identify patterns, issues, or configurations that may impact system behavior. The attributes include operating systems, software applications, and system issues, which are used to generate insights or recommendations for optimizing system performance or resolving problems. The system may compare attributes across different systems to detect anomalies, vulnerabilities, or inefficiencies. For example, it can identify outdated software versions, missing security patches, or conflicting applications that may cause instability. The collected data can be used to generate reports, alerts, or automated remediation actions to address detected issues. The system may also support predictive analytics to anticipate potential problems before they occur, allowing for proactive maintenance. By analyzing attributes such as operating systems, software applications, and system issues, the system helps administrators maintain consistent configurations, enforce security policies, and improve overall system reliability. The solution is particularly useful in environments with multiple interconnected systems where maintaining uniformity and security is critical. The system may be deployed in enterprise networks, cloud environments, or distributed computing infrastructures to ensure consistent performance and security across all systems.
3. The medium of claim 1 , wherein the operations further comprise: determining a performance metric based on the first set of data detected from the first system.
This invention relates to a system for monitoring and analyzing performance data from a computing system. The problem addressed is the need for efficient and accurate performance assessment of computing systems to optimize operations and identify potential issues. The system involves a medium, such as a non-transitory computer-readable storage medium, containing instructions that, when executed, perform operations to collect and analyze performance data. The operations include detecting a first set of data from a first computing system, where this data represents performance metrics such as processing speed, memory usage, or network latency. The system then determines a performance metric based on this detected data, which can be used to evaluate the system's efficiency, reliability, or other operational characteristics. The performance metric may be derived through statistical analysis, machine learning models, or other computational techniques to provide actionable insights. Additionally, the system may compare the performance metric against predefined thresholds or historical data to identify deviations or trends. This allows for proactive maintenance, troubleshooting, or optimization of the computing system. The system may also generate alerts or reports based on the analysis to inform administrators or automated management tools. The invention enhances the ability to monitor and improve computing system performance by providing detailed, data-driven insights into system behavior. This helps in reducing downtime, improving efficiency, and ensuring reliable operation.
4. The medium of claim 1 , wherein the operations further comprise: generating a report based on the first set of data detected from the first system.
This invention relates to data processing systems that monitor and analyze operational data from multiple systems to generate actionable insights. The problem addressed is the lack of automated tools for collecting, correlating, and reporting data from disparate systems to improve operational efficiency and decision-making. The invention involves a computer-readable medium storing instructions that, when executed, perform operations to detect a first set of data from a first system and a second set of data from a second system. The operations include analyzing the first and second sets of data to identify correlations or patterns, then generating a report based on the detected data. The report may include visualizations, statistical summaries, or alerts to highlight key findings. The system can also compare the detected data against predefined thresholds or historical data to identify anomalies or trends. The operations may further involve storing the analyzed data for future reference or integrating it with other data sources to provide a comprehensive view of system performance. The invention aims to automate data collection and analysis, reducing manual effort and improving the accuracy of operational insights.
5. The medium of claim 4 , wherein the operations further comprise: tagging a value in the report with a searchable tag.
A system and method for enhancing data reports with searchable tags to improve information retrieval and analysis. The technology addresses the challenge of efficiently locating and extracting specific data points within large, complex reports, which can be time-consuming and error-prone when relying solely on manual searches or unstructured data formats. The invention involves generating a report containing data values and associating those values with searchable tags. These tags are metadata labels that categorize or describe the data, enabling users to quickly filter, sort, or query the report based on the tagged values. The system may also include a user interface for applying, modifying, or removing tags, as well as a search function that leverages the tags to retrieve relevant data. This approach streamlines data analysis by reducing the need for manual scanning and improving the accuracy of searches within reports. The tagged values can be stored in a structured format, such as a database or a file, to ensure compatibility with existing data processing tools. The invention is applicable in fields like business intelligence, financial reporting, and scientific research, where efficient data retrieval is critical.
6. The medium of claim 1 , wherein the first probe is associated with a probe description that identifies the second set of attributes.
This invention relates to a system for managing and analyzing data probes in a technical or scientific context. The problem addressed is the need to efficiently organize and retrieve probe-related information, particularly when probes are associated with multiple attributes that must be tracked and accessed. The system involves a storage medium containing data related to probes, where each probe is associated with a set of attributes. A first probe is linked to a probe description that specifically identifies a second set of attributes. This second set of attributes may include technical specifications, operational parameters, or other relevant details that distinguish the probe from others. The probe description serves as a reference point, allowing users to quickly access the associated attributes without manually searching through unrelated data. The system ensures that the probe description is stored in a structured format, enabling efficient retrieval and processing. This structured approach helps streamline workflows in fields such as scientific research, medical diagnostics, or industrial testing, where probe attributes must be accurately tracked and analyzed. The invention improves data management by reducing redundancy and enhancing accessibility, making it easier to maintain and update probe-related information.
7. The medium of claim 1 , wherein the second set of attributes is determined based on auto-detection.
A system and method for managing data attributes in a computing environment involves dynamically determining and applying attribute sets to optimize data processing. The technology addresses inefficiencies in static attribute assignment, which can lead to suboptimal performance, resource waste, or compatibility issues. The invention automatically detects relevant attributes for a second set of data attributes, ensuring they are tailored to the specific context or requirements of the system. This auto-detection process may involve analyzing data patterns, system capabilities, or user preferences to identify the most suitable attributes. The system then applies these attributes to enhance data handling, such as improving searchability, storage efficiency, or interoperability. The auto-detection mechanism may use machine learning, rule-based logic, or heuristic analysis to determine the optimal attributes. This dynamic approach ensures that the attributes remain relevant and effective as conditions change, improving overall system performance and adaptability. The invention is particularly useful in environments where data attributes must frequently adapt to varying conditions or requirements.
8. The medium of claim 7 , wherein the auto-detection of the second set of attributes is based on at least one of: (a) a type of the first set of data detected by the first probe, (b) operations to be performed by the first probe, and (c) a computing language in which the first probe is written.
This invention relates to automated data processing systems that use probes to detect and analyze data attributes. The problem addressed is the need for efficient and accurate auto-detection of data attributes in complex computing environments, where manual configuration is time-consuming and error-prone. The system includes a first probe that detects a first set of attributes from a data source. A second probe is then deployed to auto-detect a second set of attributes based on specific criteria. The auto-detection process is determined by at least one of three factors: the type of data detected by the first probe, the operations the first probe is configured to perform, or the programming language in which the first probe is written. This ensures that the second probe is optimized for the detected data type, the intended operations, or the probe's implementation language, improving accuracy and efficiency. The system may also include a user interface for configuring the probes and a storage system for retaining the detected attributes. The probes can be dynamically adjusted based on the auto-detected attributes, allowing the system to adapt to different data environments without manual intervention. This approach reduces configuration overhead and enhances the reliability of data processing tasks.
9. The medium of claim 1 , wherein the second set of attributes is determined based on manual classification.
A system and method for data processing involves classifying data attributes to improve data analysis. The technology addresses the challenge of efficiently categorizing large datasets by leveraging both automated and manual classification techniques. The system processes a dataset containing a first set of attributes, which are initially classified using automated methods. A second set of attributes is then determined through manual classification, allowing for more precise and context-aware categorization. The manual classification step ensures that attributes not easily identified by automated systems are accurately labeled, enhancing the overall quality of the dataset. The system may also include a user interface for manual classification, enabling users to review and refine attribute classifications. This hybrid approach combines the speed of automated classification with the accuracy of human input, improving data reliability for subsequent analysis tasks. The system is particularly useful in applications requiring high-precision data categorization, such as machine learning, data mining, and knowledge management.
10. The medium of claim 1 , wherein determining that there is the overlap between the one or more attributes of the first set of attributes and the one or more attributes of the second set of attributes comprises: determining a match between (a) one or more of the second set of attributes, and (b) one or more of the first set of attributes of the first system.
This invention relates to systems and methods for detecting overlaps between attributes of different systems to improve compatibility or interoperability. The technology addresses the challenge of identifying shared or compatible attributes between two systems, which is critical in fields such as software integration, hardware compatibility, or data mapping. The invention focuses on comparing attribute sets from two systems to determine if there is a match, enabling seamless interaction or integration between them. The method involves analyzing a first set of attributes from a first system and a second set of attributes from a second system. The core innovation lies in determining whether there is an overlap by identifying a match between one or more attributes of the second set and one or more attributes of the first set. This comparison process ensures that the systems can recognize shared or compatible attributes, facilitating smoother integration or operation. The solution is particularly useful in scenarios where systems must dynamically adapt to each other’s configurations, such as in cloud computing, IoT device networks, or enterprise software ecosystems. By automating the detection of attribute overlaps, the invention reduces manual configuration efforts and minimizes compatibility errors.
11. The medium of claim 1 , wherein the operations further comprise: determining a third set of one or more attributes of a second system to be monitored; based on the second set of attributes of the second system, determining that the first probe, from the plurality of probes, includes functionality to detect a second set of data from the second system; and responsive to determining that the first probe includes the functionality to detect the second set of data from the second system: detecting the second set of data from the second system using the first probe.
This invention relates to monitoring systems, specifically to dynamically selecting and utilizing probes to gather data from multiple systems. The problem addressed is the inefficiency of traditional monitoring approaches that require pre-configured probes or manual selection, which can be inflexible and time-consuming when dealing with diverse systems. The invention involves a method for monitoring systems by dynamically determining the attributes of a system to be monitored and selecting an appropriate probe from a plurality of probes based on those attributes. The system attributes are used to identify which probe has the necessary functionality to detect specific data from the system. Once a suitable probe is identified, it is used to collect the required data. This approach allows for automated and adaptive monitoring, reducing the need for manual configuration and improving efficiency. The method includes determining a set of attributes for a system to be monitored, identifying a probe that can detect the desired data based on those attributes, and then using that probe to gather the data. This dynamic selection process ensures that the most suitable probe is used for each system, optimizing monitoring performance and accuracy. The invention also supports monitoring multiple systems with varying attributes, enhancing scalability and adaptability in monitoring environments.
12. The medium of claim 11 , wherein: the first set of attributes of the first system and the third set of attributes of the second system include a common attribute; the first probe is identified as including functionality to detect the first set of data from the first system and the second set of data from the second system based at least on the common attribute.
This invention relates to a system for detecting and correlating data from multiple systems using shared attributes. The problem addressed is the difficulty in identifying and extracting relevant data from disparate systems that may have overlapping but not identical attributes. The solution involves a medium, such as a storage device or memory, that stores instructions for a probe to detect data from two or more systems. The probe is configured to identify a common attribute shared between the first system's attributes and the second system's attributes. Based on this common attribute, the probe is designed to detect a first set of data from the first system and a second set of data from the second system. The probe's functionality is determined at least in part by this common attribute, ensuring that the data collected from both systems is relevant and comparable. This approach enables more accurate and efficient data correlation across different systems, improving decision-making and system integration. The invention may be used in environments where multiple systems need to share or synchronize data, such as in enterprise IT, cybersecurity, or industrial automation.
13. The medium of claim 1 , wherein the operations further comprise: based on the first set of attributes of the first system, determining that a second probe, of the plurality of probes, does not include functionality to detect a second set of data from the first system; refraining from using the second probe to detect any data from the first system.
This invention relates to a system for selectively deploying probes to monitor or analyze a target system based on the system's attributes. The problem addressed is the inefficiency of using probes that lack the necessary functionality to detect specific data from the target system, which can waste computational resources and degrade performance. The system includes a plurality of probes, each designed to detect different sets of data from the target system. Each probe has a defined set of attributes that determine its capabilities. The system first identifies a first set of attributes of the target system, which describe its configuration, capabilities, or other relevant characteristics. Based on these attributes, the system determines whether a second probe, from the plurality of probes, lacks the necessary functionality to detect a second set of data from the target system. If the second probe cannot detect the required data, the system refrains from using it, thereby optimizing resource usage and avoiding unnecessary operations. This selective deployment ensures that only probes with the appropriate capabilities are used, improving efficiency and accuracy in data detection. The system may also include additional probes with different functionalities, each evaluated similarly based on the target system's attributes.
14. The medium of claim 1 , wherein: the first set of attributes of the first system comprises at least one of: (a) an operating system, (b) a software application, and (c) an issue associated with the first system; the first probe is associated with a probe description that identifies the second set of attributes comprising a first attribute and a second attribute; the first attribute, associated with the first probe, is determined using auto-detection based on at least one of: (a) a type of the first set of data detected by the first probe, (b) operations to be performed by the first probe, and (c) a computing language in which the first probe is written; the second attribute, associated with the first probe, is determined using manual classification; determining that there is the overlap between the one or more attributes of the first set of attributes and the one or more attributes of the second set of attributes comprises: determining a match between (a) one or more of the second set of attributes, and (b) one or more of the first set of attributes of the first system; the operations further comprise: determining a performance metric based on the first set of data detected from the first system; generating a report based on the first set of data detected from the first system; tagging a value in the report with a searchable tag; determining a third set of one or more attributes of a second system to be monitored, wherein the first set of attributes of the first system and the second set of attributes of the second system include a common attribute; based at least on the common attribute, determining that the first probe, of the plurality of probes, includes functionality to detect a second set of data from the second system; and responsive to determining that the first probe includes the functionality to detect the second set of data from the second system: detecting the second set of data from the second system using the first probe; based on the first set of attributes of the first system, determining that a second probe, of the plurality of probes, does not include functionality to detect a third set of data from the first system; refraining from using the second probe to detect any data from the first system.
This invention relates to a system for monitoring and analyzing attributes of computing systems using probes. The system addresses the challenge of efficiently detecting and processing relevant data from diverse computing environments by leveraging both automated and manual classification of probe attributes. The system includes a plurality of probes, each associated with a probe description that identifies a set of attributes, such as operating systems, software applications, or system issues. These attributes are determined through auto-detection based on factors like the type of data detected, the probe's operations, or its programming language, as well as manual classification. The system compares the attributes of a target system (e.g., an operating system or application) with the attributes of available probes to identify overlaps, ensuring that only relevant probes are used for data collection. Once a suitable probe is identified, it detects data from the system, generates performance metrics, and produces a report with searchable tags. The system also extends this functionality to multiple systems by identifying common attributes between them, allowing the same probe to monitor different systems when applicable. Additionally, the system avoids unnecessary data collection by refraining from using probes that lack the required functionality for a given system. This approach optimizes monitoring efficiency and accuracy by dynamically matching probes to system attributes.
15. The medium of claim 1 , wherein: the first set of attributes includes an issue, associated with the first system, which is identified based on historical data related to the first system; and the second set of attributes includes the issue associated with the systems for which the first probe includes the functionality to monitor.
This invention relates to a system for monitoring and managing issues across multiple systems using probes with configurable attributes. The technology addresses the challenge of efficiently identifying and tracking system issues by leveraging historical data and probe capabilities. The system includes a medium storing instructions for a first probe that monitors a first system and other systems. The first probe has a first set of attributes, including an issue identified from historical data related to the first system. The second set of attributes pertains to issues that the first probe is capable of monitoring in other systems. The probe's functionality is dynamically adjusted based on these attributes to ensure comprehensive monitoring. The system ensures that issues are detected early and monitored consistently across multiple systems, improving system reliability and reducing downtime. The historical data analysis allows for proactive issue identification, while the probe's adaptability ensures it can monitor relevant issues across different systems. This approach enhances system management by integrating historical insights with real-time monitoring capabilities.
16. A system, comprising: at least one device including a hardware processor; the system being configured to perform operations comprising: determining a first set of one or more attributes of a first system to be monitored; identifying a first probe, of a plurality of probes, includes functionality to monitor systems with a second set of one or more attributes; determining there is an overlap between one or more attributes of the first set of attributes and one or more attributes of the second set of attributes; responsive at least to determining that there is the overlap between the one or more attributes of the first set of attributes and the one or more attributes of the second set of attributes: selecting the first probe for monitoring the first system; detecting a first set of data from the first system using the first probe.
The system relates to automated monitoring of computer systems by selecting appropriate monitoring probes based on system attributes. The problem addressed is the inefficiency of manually selecting monitoring tools for diverse systems, which can lead to incorrect or incomplete monitoring data. The system includes a hardware processor that determines the attributes of a target system to be monitored, such as operating system type, software versions, or network configurations. It then identifies a probe from a pool of available probes that has the necessary functionality to monitor systems with matching attributes. The system checks for an overlap between the target system's attributes and the probe's supported attributes. If a sufficient match is found, the system selects the probe for monitoring the target system and collects data from it. This automated selection ensures that the most suitable probe is used, improving monitoring accuracy and reducing manual intervention. The system may also support dynamic adjustments if system attributes change over time. The approach enhances scalability and reliability in monitoring heterogeneous environments.
17. The system of claim 16 , wherein the first set of attributes of the first system comprises at least one of: (a) an operating system, (b) a software application, and (c) an issue associated with the first system.
This invention relates to a system for managing and analyzing attributes of computing systems to improve performance, security, or functionality. The system collects and processes attributes from multiple computing systems to identify patterns, issues, or configurations that may impact system behavior. The attributes include operating systems, software applications, and issues affecting the systems. By analyzing these attributes, the system can detect vulnerabilities, optimize performance, or recommend corrective actions. The system may also compare attributes across different systems to identify inconsistencies or best practices. This approach helps administrators maintain system health, reduce downtime, and enhance security by proactively addressing potential problems. The system may integrate with existing monitoring tools or databases to provide a centralized view of system attributes and their impact on overall performance. The analysis can be automated or manually triggered, allowing for both real-time and scheduled assessments. The system supports various types of computing environments, including servers, workstations, and embedded systems, making it adaptable to different use cases.
18. The system of claim 16 , wherein the operations further comprise: determining a performance metric based on the first set of data detected from the first system.
A system monitors and analyzes data from a first system to detect anomalies or performance issues. The system collects a first set of data from the first system, processes this data to identify patterns or deviations, and generates alerts or recommendations based on the analysis. The system may also compare the detected data against predefined thresholds or historical data to assess performance. Additionally, the system determines a performance metric derived from the first set of data, which quantifies the efficiency, reliability, or operational status of the first system. This metric can be used for further analysis, reporting, or decision-making to optimize system performance. The system may also include interfaces for user interaction, allowing operators to view detected data, performance metrics, and generated alerts. The system may further integrate with other systems or databases to enhance data collection, processing, or reporting capabilities. The performance metric can be used to trigger automated actions, such as adjustments to system parameters or notifications to maintenance personnel. The system ensures continuous monitoring and proactive management of the first system to prevent failures or inefficiencies.
19. A method, comprising: determining a first set of one or more attributes of a first system to be monitored; identifying a first probe, of a plurality of probes, includes functionality to monitor systems with a second set of one or more attributes; determining there is an overlap between one or more attributes of the first set of attributes and one or more attributes of the second set of attributes; responsive at least to determining that there is the overlap between the one or more attributes of the first set of attributes and the one or more attributes of the second set of attributes: selecting the first probe for monitoring the first system; detecting a first set of data from the first system using the first probe; wherein the method is performed by at least one device including a hardware processor.
The invention relates to automated system monitoring using probes. The problem addressed is efficiently selecting appropriate monitoring tools for diverse systems with varying attributes. The method involves analyzing a system to be monitored by determining its attributes, such as hardware specifications, software versions, or network configurations. A pool of available monitoring probes is evaluated to identify probes capable of monitoring systems with matching attributes. The method checks for overlaps between the system's attributes and the probe's supported attributes. If a sufficient match is found, the probe is selected to monitor the system, and data is collected accordingly. The process ensures that only compatible probes are used, improving monitoring accuracy and reducing errors. The method is executed by a computing device with a hardware processor, enabling automated and scalable system monitoring. This approach optimizes resource allocation by dynamically matching probes to systems based on their attributes, enhancing efficiency in large-scale monitoring environments.
20. The method of claim 19 , wherein the first set of attributes of the first system comprises at least one of: (a) an operating system, (b) a software application, and (c) an issue associated with the first system.
This invention relates to a method for analyzing and managing system attributes in a computing environment. The method addresses the challenge of efficiently identifying and categorizing key characteristics of a system to facilitate troubleshooting, compatibility checks, or system management. The system attributes include an operating system, software applications, and issues associated with the system. These attributes are used to determine compatibility, diagnose problems, or optimize performance. The method involves collecting and processing these attributes to generate actionable insights or recommendations. For example, the operating system attribute helps assess software compatibility, while the software application attribute identifies installed programs that may require updates or patches. The issue attribute captures known problems or errors, enabling proactive resolution. By systematically analyzing these attributes, the method improves system reliability, reduces downtime, and enhances user experience. The approach is applicable to various computing environments, including personal computers, servers, and embedded systems. The invention ensures that system attributes are accurately captured and utilized to support decision-making in IT operations.
21. The method of claim 19 , further comprising: determining a performance metric based on the first set of data detected from the first system.
A system and method for monitoring and analyzing performance metrics in a technical environment involves detecting data from a first system and a second system, where the second system is configured to interact with the first system. The method includes processing the detected data to identify a set of events or conditions relevant to the operation of the first system. The system may use sensors, log files, or other monitoring tools to gather this data. The method further includes determining a performance metric based on the detected data from the first system. This performance metric could measure efficiency, reliability, response time, or other operational characteristics. The system may compare the performance metric against predefined thresholds or historical data to assess system health. The method may also involve generating alerts or recommendations based on the analysis, allowing for proactive maintenance or optimization. The system may be applied in industrial control systems, IT infrastructure, or other domains where performance monitoring is critical. The goal is to improve system reliability, reduce downtime, and enhance overall operational efficiency by continuously analyzing performance data.
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December 1, 2020
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